ISSN 0439-755X
CN 11-1911/B
主办:中国心理学会
   中国科学院心理研究所
出版:科学出版社

心理学报 ›› 2024, Vol. 56 ›› Issue (2): 194-209.doi: 10.3724/SP.J.1041.2024.00194

• “数智时代的道德伦理”特刊 • 上一篇    下一篇

机器人遵从伦理促进人机信任?决策类型反转效应与人机投射假说

王晨1, 陈为聪2,3, 黄亮2,3(), 侯苏豫2,3, 王益文4()   

  1. 1.福州大学经济与管理学院, 福州 350116
    2.闽南师范大学应用心理研究所, 漳州 363000
    3.福建省应用认知与人格重点实验室, 漳州 363000
    4.上海财经大学数字经济系, 上海 200433
  • 收稿日期:2022-07-04 发布日期:2023-12-01 出版日期:2024-02-25
  • 通讯作者: 王益文, E-mail: wangeven@126.com;黄亮, E-mail: yeoo5860@163.com
  • 基金资助:
    *国家社会科学基金重大项目(19ZDA361);国家社会科学基金青年项目(20CSH069)

Robots abide by ethical principles promote human-robot trust? The reverse effect of decision types and the human-robot projection hypothesis

WANG Chen1, CHEN Weicong2,3, HUANG Liang2,3(), HOU Suyu2,3, WANG Yiwen4()   

  1. 1. School of Economics and Management, Fuzhou University, Fuzhou 350116, China
    2. Institute of Applied Psychology, Minnan Normal University, Zhangzhou 363000, China
    3. Fujian Key Laboratory of Applied Cognition and Personality, Zhangzhou 363000, China
    4. Department of Digital Economics, Shanghai University of Finance and Economics, Shanghai 200433, China
  • Received:2022-07-04 Online:2023-12-01 Published:2024-02-25

摘要:

阿西莫夫三大伦理原则是关于人工智能机器人的基本伦理规范。本研究提出人机投射假说——人会从自身具有的认知、情感和行动智能出发, 去理解机器人的智能并与之互动。通过3个实验, 从原则一到原则三逐步考察在机器人是否遵守伦理原则对人机信任的影响中, 机器人决策类型(作为与否; 服从人类命令与否; 保护自身与否)的效应, 以及人机投射的潜在机制。结果揭示了人机投射在机器人遵守伦理原则促进人机信任中起中介作用, 以及机器人决策类型与是否遵守伦理原则之间有趣且有意义的交互效应: (1)在遵守情境下, 机器人作为相对于不作为更有利于促进信任, 但在违反情境下, 则反之; (2)在遵守且尤其在违反情境下, 机器人服从相比不服从人类命令更有利于促进人机信任; (3)相较于违反情境, 机器人保护相比不保护自身在遵守情境下更有利于促进人机信任。跨实验的分析更深入地阐释了在遵守和违反伦理原则情境中以及伦理要求冲突情境中, 有利于促进人机信任的机器人行动决策因素。

关键词: 人工智能, 机器人伦理原则, 人机信任, 人机投射, 人机交互

Abstract:

Asimov's Three Laws of Robotics are the basic ethical principles of artificial intelligent robots. The ethic of robots is a significant factor that influences people’s trust in human-robot interaction. Yet how it affects people's trust, is poorly understood. In this article, we present a new hypothesis for interpreting the effect of robots’ ethics on human-robot trust—what we call the human-robot projection hypothesis (HRP hypothesis). In this hypothesis, people are based on their intelligence, e.g., intelligence for cognition, emotion, and action, to understand robots’ intelligence and interact with them. We propose that compared with robots that violate ethical principles, people project more mind energy (i.e., the level of mental capacity of humans) onto robots that abide by ethical principles, thus promoting human-robot trust.

In this study, we conducted three experiments to explore how presenting scenarios where a robot abided by or violated Asimov’s principles would affect people’s trust in the robot. Meanwhile, each experiment corresponds to one of Asimov’s principles to explore the interaction effect of the types of robot’s decisions. Specifically, all three experiments were two by two experimental designs. The first within-subjects factor was whether the robot being interacted with had abided by Asimov’s principle with a “no harm” core element. The second within-subjects factor was the types of robot’s decision, with corresponding differences in Asimov’s principles among different experiments (Experiment 1: whether the robot takes action or not; Experiment 2: whether the robot obeys human’s order or not; Experiment 3: whether the robot protects itself or not). We assessed the human-robot trust by using the trust game paradigm.

Experiments 1-3 consistently showed that people were more willing to trust robots that abided by ethical principles compared with those who violated. We also found that human-robot projection played a mediating role, which supports the HRP hypothesis. In addition, the significant interaction effects between the type of robot’s decision and robot abided by or violated Asimov’s principle existed in all three experiments. The results of Experiment 1 showed that action robots got more trust than inaction robots when abided by the first principle, whereas inaction robots got more trust than action robots when they violated the first principle. The results of Experiment 2 showed that disobeyed robots got less trust than obeyed robots. The detrimental effect was greater in scenarios where robots violated the second principle than in those who abided. The results of Experiment 3 showed that compared with robots that violated the third principle, the trust-promoting effect of protecting itself versus destroying itself was stronger among those who abided. The above results indicated that the reverse effects of decision types existed in both Experiments 1 and 3. Finally, the cross-experimental analysis showed that: (1) When robots abided by ethical principles, their inaction and disobedience still compromise human-robot trust. When robots violated ethical principles, their obedience incurs the least loss of human-robot trust, while their action and disobedience incur a relatively severe loss of human-robot trust. (2) When the ethical requirements of different robotic laws conflict, there was no significant difference between the importance of not harming humans and obeying human orders in terms of the human-robot trust, and both were more important than protecting robots themselves.

This study helps to understand the impact of robotic ethical decision-making on human-robot trust and the important role of human-robot projection, which might have important implications for future research in human-robot interaction.

Key words: artificial intelligence, laws of robotics, human-robot trust, human-robot projection, human-robot interaction

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